CONICAL

The Computational Neuroscience
Class Library

CONICAL is a C++ class library for building simulations
common in computational neuroscience. Currently its focus is on
compartmental modeling, with capabilities similar to GENESIS and NEURON.
Future classes may support reaction-diffusion kinetics and more.

A key feature of CONICAL is its cross-platform
compatibility; it has been fully co-developed and tested under
Unix, DOS, and Mac OS. Any C++ compiler which adheres to the emerging
ANSI standard should be able to compile the CONICAL classes
without modification.

CONICAL is intended to encourage the rapid development
of simulator software, especially on non-Unix systems where such software
is sorely lacking. The library may be freely used within certain
restrictions (write for details).

Why another neural modeling package?

CONICAL is not a direct competitor with other neural
simulation software; rather it serves different purposes. Whereas
other packages are generally self-contained programs for a particular
platform, CONICAL is a back-end simulation engine around
which a number of neural modeling applications can be built. As shown in
the table below, each approach has its pros and cons:

Typical Simulator App

CONICAL

Platform

Unix/X-Windows

Any

Model Building

Unique Script Language

C++

Interface

Various

Text/File Only

Customization

Difficult

Easy

Intended Users

Researchers

Researchers, Teachers,
Students, & Programmers

Since simulator applications usually attempt to provide a graphical
interface, they have to choose a platform, and this is usually X-Windows
so that the high-powered Unix workstations common in research labs can be
used. By separating interface from engine, CONICAL
sidesteps this choice, and can use fully portable code. And though its
use requires writing C++ code, this is a common language, which can make
CONICAL easier to learn than other script-based
simulators.

CONICAL is no longer under active development, but the code may still serve as a good starting point for computational modeling or for educational purposes. The
documentation
reflects the current state of the library.
See the
release
notes for latest version information.